A Bridgeless, Stacked Switch-Pair-Based AC/DC On-Board High-Voltage EV Charger With Minimal Storage Capacitance Featuring Continuous Secondary-Side High-Frequency Rectifier Control
Bibliographic record
Abstract
In this paper, a fully soft-switched single-stage bridgeless stacked switches-based rectifier with reduced storage capacitance and minimized low-frequency output voltage ripple for high-voltage (HV) Electric Vehicle (EV) systems is proposed. Generally, bulky DC-link and filter electrolytic-type capacitors used in AC-DC converters reduces the converter’s reliability and life-span. To address this issue, a bridgeless AC-DC isolated converter with stacked switches configuration on both the primary and secondary sides that employs a continuous secondary side duty ratio control to reduce the low frequency output voltage ripple is presented. A front-end primary side duty ratio control for achieving power factor correction (PFC) for the integrated bridgeless boost PFC is also employed. The stacked switches-based configuration of the converter reduces the voltage stress of the switches to half of the DC-link voltage, making the converter suitable for HV battery systems. Soft-switching operation is guaranteed for all the semiconductor devices. Additionally, output voltage regulation is achieved through a Variable Frequency (VF) control on the primary-side switches. The steady-state and dynamic performance of the proposed converter and the designed control system are verified using a 1.1kW, 120Vrms/800Vdc, 100-120kHz SiC proof-of-Concept proto-type in the laboratory.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".